• Dr.V. Mohan Nayak
• Palla Rajyalakshmi

Artificial Intelligence (AI) is transforming how organizations assess, monitor, and enhance employee performance. Traditional performance management systems, often criticized for their subjectivity, infrequent feedback cycles, and lack of real-time insights, are being replaced or augmented by AI-driven solutions. These solutions leverage machine learning, natural language processing, and predictive analytics to automate evaluations, provide real-time feedback, and create personalized employee development plans. AI systems are increasingly used to identify performance trends, predict potential issues, and recommend interventions, enabling data-driven decision-making for both employees and management. This paper explores the need, scope, and significance of integrating AI in performance management systems. It presents the current status, advantages, and limitations, based on secondary data and literature reviews. Key findings reveal how AI improves transparency, reduces bias, and enhances productivity through continuous feedback loops. However, challenges such as data privacy, algorithmic bias, and employee resistance persist. The paper concludes by offering suggestions for ethical, effective implementation of AI tools in performance systems to foster a culture of innovation, growth, and accountability in modern organizations.

Artificial Intelligence, Performance Management, Feedback Systems, Human Resource Technology, Predictive Analytics, Employee Evaluation, AI in HRM

"TRANSFORMING PERFORMANCE MANAGEMENT: THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN FEEDBACK SYSTEMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.315-319, August-2025, Available :http://www.jetir.org/papers/JETIRHC06047.pdf

"TRANSFORMING PERFORMANCE MANAGEMENT: THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN FEEDBACK SYSTEMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. pp315-319, August-2025, Available at : http://www.jetir.org/papers/JETIRHC06047.pdf